Instance Similarity Learning for Unsupervised Feature Representation
Instance Similarity Learning for Unsupervised Feature Representation
In this paper, we propose an instance similarity learning (ISL) method for unsupervised feature representation. Conventional methods assign close instance pairs in the feature space with high similarity, which usually leads to wrong pairwise relationship for large neighborhoods because the Euclidean distance fails to depict the true semantic similarity on …